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4.2 0.5 4.6 5.2 2.7 4.2 1.8 1.7 3.8 0 3.9 3.5 1 1.7 7.8 4.9 3.8 0 7.7 0 7.7 0 10.1 1.7 0 8.6 3.9 4.2 1.7 0 7 1.8 8.4 3.4 7 3.9 2.7 7.7 1.7 1.7 11 1.8 2.1 0.7 1.7 10.5 6.2 1.8 1.7 7 3.5 3.8 0.5 1.8 8.4 7.7 1.7 4.9 0 1.8 6.3 5.2 1 1 0 5.6 5.6 3.8 3.5 6.3 0 5.9 1.7 3.5 1.8 0 8.4 5.1 7 3.4 4.2 0 1.4 3.9 6.3 7 2.1 4.5 0 3.5 8.1 4.2 0 1.7 5.3 1.8 0 13.6 9.4 0 2.1 1.7 2.1 0 3.5 1.8 0 8 0 2.1 3.9 1 7.7 2.1 1.7 0 1 6 0 1.8 3.5 4.2 7.6 1 1.8 2.1 1 1.7 8.4 10.8 1.8 2.1 0 0.7 5.6 6 1.7 1.8 5.2 6.3 0 3.4 1 1 5.6 8.3 2.6 2.1 0 3.5 8.3 7 3.4 1 4.2
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R Code
library(MASS) library(car) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() bitmap(file='test3.png') qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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